[scikit-image] regarding the parameter of clip_limit for applying contrast limited adaptive historgram equalization

[Egor Panfilov]

Dear Yuanyuan,

There is no strict correspondence between these two clip limits.
If you would like to have something like OpenCV implementation of CLAHE,
consider trying https://github.com/anntzer/clahe.
Also, feel free to join the discussion in https://github.com/scikit-i
mage/scikit-image/issues/2219. There you might find a bit more details.

Regards,
Egor

2016-12-27 2:22 GMT+03:00 wine lover <winecoding at gmail.com>:

> Dear All,
>
> The following is an example given in opencv regarding applying Contrast
> Limited Adaptive Histogram Equalization (CLAHE)
>
> *import numpy as np*
> *import cv2*
> *img = cv2.imread('tsukuba_l.png',0)*
> *clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))*
> *cl1 = clahe.apply(img)*
>
> Here the parameter clipLimit =2.0
>
> In Skimage, CLAHE  is perfored using *exposure.equalize_adapthist*
>
> For instance, in this example, http://scikit-image.org/docs/
> dev/auto_examples/plot_equalize.html
>
> *img_adapteq = exposure.equalize_adapthist(img, clip_limit=0.03)*
>
> My question is that how to setup the clip_limit value in skimage for a
> corresponding case in opencv
>
>
> For instance, in an example implemented using opencv, clipLimit is setup
> as 2.0; if I want to convert this implementation using skimage
> which value should I assign to clip_limit?
>
> According to the document  looks like clip_limit between 0 and 1.
> *clip_limit : float, optional*
> *Clipping limit, normalized between 0 and 1 (higher values give more
> contrast).*
>
> while opencv does not have this limitation for clipLimit
>
> Thanks,
> Yuanyuan
>
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>
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